Poster No:
276
Submission Type:
Abstract Submission
Authors:
Katharina Wittfeld1, Stefan Frenzel1, Alexander Teumer1, Marcus Dörr2, Martin Bahls2, Robin Bülow3, Matthias Nauck4, Henry Völzke5, Deborah Janowitz6, Hans Grabe1
Institutions:
1University Medicine Greifswald, Department of Psychiatry and Psychotherapy, Greifswald, Mecklenburg-Vorpommern, 2University Medicine Greifswald, Department of Internal Medicine B, Greifswald, Mecklenburg-Vorpommern, 3University Medicine Greifswald, Institute of Diagnostic Radiology and Neuroradiology, Greifswald, Mecklenburg-Vorpommern, 4University Medicine Greifswald, Institute of Clinical Chemistry and Laboratory Medicine, Greifswald, Mecklenburg-Vorpommern, 5University Medicine Greifswald, Institute for Community Medicine, Greifswald, Mecklenburg-Vorpommern, 6Clinical Centre for Psychiatry und Psychotherapy, Site West, Stralsund, Stralsund, Mecklenburg-Vorpommern
First Author:
Katharina Wittfeld
University Medicine Greifswald, Department of Psychiatry and Psychotherapy
Greifswald, Mecklenburg-Vorpommern
Co-Author(s):
Stefan Frenzel
University Medicine Greifswald, Department of Psychiatry and Psychotherapy
Greifswald, Mecklenburg-Vorpommern
Alexander Teumer
University Medicine Greifswald, Department of Psychiatry and Psychotherapy
Greifswald, Mecklenburg-Vorpommern
Marcus Dörr
University Medicine Greifswald, Department of Internal Medicine B
Greifswald, Mecklenburg-Vorpommern
Martin Bahls
University Medicine Greifswald, Department of Internal Medicine B
Greifswald, Mecklenburg-Vorpommern
Robin Bülow
University Medicine Greifswald, Institute of Diagnostic Radiology and Neuroradiology
Greifswald, Mecklenburg-Vorpommern
Matthias Nauck
University Medicine Greifswald, Institute of Clinical Chemistry and Laboratory Medicine
Greifswald, Mecklenburg-Vorpommern
Henry Völzke
University Medicine Greifswald, Institute for Community Medicine
Greifswald, Mecklenburg-Vorpommern
Deborah Janowitz
Clinical Centre for Psychiatry und Psychotherapy, Site West, Stralsund
Stralsund, Mecklenburg-Vorpommern
Hans Grabe
University Medicine Greifswald, Department of Psychiatry and Psychotherapy
Greifswald, Mecklenburg-Vorpommern
Introduction:
According to the World Health Organization, dementia is currently affecting over 55 million people with nearly 10 million new cases every year (WHO, 2023). Modifiable risk factors are in the focus of the scientific community to prevent dementia or postpone its onset which would reduce the personal and economic burden.
During the last years, the heart-brain-axis captured increasing attention. Accumulating evidence supports the hypothesis that vascular and degenerative structural brain changes might function as a link between cardiac disease and cognitive impairment. (Jensen, 2023; Frenzel, 2021; Veugen, 2018; Sabayan, 2015). Within these studies, cardiac diseases are accessed by blood based cardiac biomarkers: natriuretic peptides (most frequently by NT-proBNP) and cardiac troponins (e.g. hs-cTnT) which are measured in clinical routines. Besides measures for specific brain damages (e.g. white matter hyperintensities (WMH), silent brain infarcts, and cerebral microbleeds), brain atrophy is studied using global brain parameters like total brain volume, total gray matter (GM) and white matter (WM).
In our work, we investigated the association of NT-proBNP and brain atrophy in a more detailed way by dividing the total GM volume into their cortical and subcortical portions and studying the different dimensions of the cortex (cortical thickness and surface area). Further, we analyzed specific brain atrophy patterns for aging and Alzheimer's Disease.
Methods:
We studied 2,995 adults aged 21-90 years from two independent population-based cohorts of the Study of Health in Pomerania (SHIP-START and SHIP-TREND). (Völzke, 2022) MRI brain data were derived from structural T1- and FLAIR-sequences. (Hosten, 2021) We used FreeSurfer 7.3.2 to determine the cortical and subcortical GM, total WM, intracranial volume (ICV), hemisphere-wide cortical thickness and surface area, and local cortical thickness (Desikan-Killiany atlas; 34 regions per hemisphere). Based on the FreeSurfer data, scores were generated that summarize the atrophy patterns linked to Alzheimer's Disease (FSAD) and brain aging (FSBA). (Frenzel, 2020; Weihs, 2021) Further, we extracted the WMH with the LST toolbox. (Schmidt, 2012)
Brain measures and atrophy scores were analyzed using regression models on log(NT-proBNP) with adjustment for age (non-linear), sex, cohort, ICV, and in sensitivity analyses additional for systolic and diastolic blood pressure, antihypertensive medication, diabetes, high and low density lipoprotein, BMI, smoking, alcohol intake, and education.
Results:
We observed significant negative correlations of NT-proBNP with the total GM cortex volume (beta_ml=-2.82, p<1E-6) and the mean cortical thickness (beta_mm=-0.01, p<1E-6) of both hemispheres. This effect corresponds to a 0.1 ml reduced cortex volume per 10% increase in NT-proBNP. All associations remained robust in the sensitivity analyses. Subcortical GM, cerebral WM, and the WM surface area of both hemispheres did not show any significant association with NT-proBNP.
Cortical thickness of over 85 % of the 68 regions defined by the Desikan-Killiany atlas reached at least nominal significance for a negative association with NT-proBNP. Additional adjustment for the mean cortical thickness of the corresponding hemisphere led to a loss in effect size and significance which points to a rather global effect on the brain than to specific local effects.
Further, higher levels of NT-proBNP were significantly associated with a higher FSAD score. The association of FSBA and NT-proBNP only reached nominal significance but points to advanced brain aging with higher levels of NT-proBNP.
We could not replicate the published findings concerning WMH, neither dimensional nor after dichotomization.
Conclusions:
In contrast to subcortical gray matter, cortical brain measures are strongly associated with circulating NT-proBNP levels in a global way.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Lifespan Development:
Aging 2
Keywords:
Aging
Cortex
Data analysis
Degenerative Disease
MRI
Plasticity
STRUCTURAL MRI
Other - heart-brain-axis, cardiac disease, cardiac biomarker
1|2Indicates the priority used for review
Provide references using author date format
Frenzel, S. (2020), ‘A Biomarker for Alzheimer’s Disease Based on Patterns of Regional Brain Atrophy’, Frontiers in Psychiatry, https://doi.org/10.3389/fpsyt.2019.00953
Frenzel, S. (2021), ‘Cardiac Hypertrophy Is Associated With Advanced Brain Aging in the General Population’, Journal of the American Heart Association, 10(17):e020994.
Hosten, N. (2021), ‘Review - SHIP-MR and Radiology: 12 Years of Whole-Body Magnetic Resonance Imaging in a Single Center’, Healthcare, 10(1): 33.
Jensen, M. (2023), ‘Circulating cardiac biomarkers, structural brain changes, and dementia: Emerging insights and perspectives’, Alzheimer's and Dementia, 19 (4):1529-1548.
Sabayan, B. (2015), ‘N-terminal pro-brain natriuretic peptide and abnormal brain aging’, Neurology, 85 (9): 813-820.
Schmidt, P. (2012), ‘An automated tool for detection of FLAIR-hyperintense white-matter lesions in multiple sclerosis’, Neuroimage, 59(4):3774–3783.
Veugen, M. (2018), ‘Cross-sectional associations between cardiac biomarkers, cognitive performance, and structural brain changes are modified by age the Maastricht study’, Arteriosclerosis, Thrombosis, and Vascular Biology, 38 (8):1948-1958.
Völzke, H. (2022), ‘Cohort Profile Update: The Study of Health in Pomerania (SHIP)’, International Journal of Epidemiology, 1-12.
Weihs, A. (2021), ‘Associations between sleep apnea and advanced brain aging in a large-scale population study’, Sleep, 44(3).
WHO (2023), https://www.who.int/news-room/fact-sheets/detail/dementia